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Astronomy

Astronomy is the study of everything in the universe beyond Earth’s atmosphere. That includes objects we can see with our naked eyes, like the Sun, the Moon, the planets, and the stars. It also contains objects we can only see with telescopes or other instruments, like faraway galaxies and tiny particles. And it even includes questions about things we can't see, like dark matter and energy.

Papers

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Showing 301–350 of 395 papers

TitleStatusHype
Astronomical Images Quality Assessment with Automated Machine Learning—0
Astronomical Pipeline Provenance: A Use Case Evaluation—0
Astronomical source finding services for the CIRASA visual analytic platform—0
AstroSpy: On detecting Fake Images in Astronomy via Joint Image-Spectral Representations—0
AstroVisBench: A Code Benchmark for Scientific Computing and Visualization in Astronomy—0
A Study on Classification in Imbalanced and Partially-Labelled Data Streams—0
A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time Series—0
At First Sight: Zero-Shot Classification of Astronomical Images with Large Multimodal Models—0
PolarRec: Radio Interferometric Data Reconstruction with Polar Coordinate Representation—0
A unified method for super-resolution recovery and real exponential-sum separation—0
Autoencoder-driven Spiral Representation Learning for Gravitational Wave Surrogate Modelling—0
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems—0
Autowarp: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders—0
A Versatile Framework for Analyzing Galaxy Image Data by Implanting Human-in-the-loop on a Large Vision Model—0
Bayesian Detection of a Sinusoidal Signal with Randomly Varying Frequency—0
Bayesian Imaging for Radio Interferometry with Score-Based Priors—0
Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy—0
Boosting the Efficiency of Parametric Detection with Hierarchical Neural Networks—0
Bridging the Gap: A Decade Review of Time-Series Clustering Methods—0
Building astroBERT, a language model for Astronomy & Astrophysics—0
Category-based Galaxy Image Generation via Diffusion Models—0
Multi-layered characterization of hot stellar systems with confidence—0
Clustering via torque balance with mass and distance—0
Clustering with phylogenetic tools in astrophysics—0
Collaboration with Cellular Networks for RFI Cancellation at Radio Telescope—0
Communication protocol for a satellite-swarm interferometer—0
Comprehensible Counterfactual Explanation on Kolmogorov-Smirnov Test—0
Compressed particle methods for expensive models with application in Astronomy and Remote Sensing—0
Compressive Sensing Using Iterative Hard Thresholding with Low Precision Data Representation: Theory and Applications—0
Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases—0
Computation of Optical Refractive Index Structure Parameter from its Statistical Definition Using Radiosonde Data—0
Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers—0
Content-Based Image Retrieval Using COSFIRE Descriptors with application to Radio Astronomy—0
Contextualization of topics - browsing through terms, authors, journals and cluster allocations—0
Crowdsourcing Predictors of Residential Electric Energy Usage—0
Cycle Generative Adversarial Networks Algorithm With Style Transfer For Image Generation—0
Cyclic Imaging for All-Sky Interference Forecasting with Array Radio Telescopes—0
Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian—0
Data-driven Influence Based Clustering of Dynamical Systems—0
Data science and Machine learning in the Clouds: A Perspective for the Future—0
Deep Learning for Energy Estimation and Particle Identification in Gamma-ray Astronomy—0
Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era—0
Deep Neural Networks to Enable Real-time Multimessenger Astrophysics—0
Deep Sky Objects Detection with Deep Learning for Electronically Assisted Astronomy—0
Deep supervised hashing for fast retrieval of radio image cubes—0
Deep Variational Semi-Supervised Novelty Detection—0
Denoising Gravitational Waves using Deep Learning with Recurrent Denoising Autoencoders—0
Deriving a Quantitative Relationship Between Resolution and Human Classification Error—0
Desaturating EUV observations of solar flaring storms—0
Detecting streaks in smart telescopes images with Deep Learning—0
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